Automated Analytics and Autologous CAR-T Cell Therapy
Arguably the biggest conference track of the event, Cell Therapy provided live and on-demand sessions exploring topics from process development and manufacturing to analytical technologies.
Maribel Rios looks back at two of the most popular sessions across the week.
Veeren Chauhan, (University of Nottingham) explained that traditional bioreactor sensors measure extracellular parameters such as pH, cellular oxygen, and metabolites to ensure that cells are growing effectively.
However, most biochemical changes that are important for cell growth occur on a subcellular level, including subcellular molecular oxygen, protons in the form of pH, carbon dioxide, and macromolecular structures such as cytokines and proteins.
New measurement technologies are needed to enable subcellular measurements, and automated analytics are needed to enhance efficacy of cell culture.
Such sensors ideally should be noninvasive and highly sensitive and provide high spatial and temporal resolutions.
Fluorescent nanosensors have been developed that can be delivered to subcellular spaces and make continual long-term measurements.
The compose of a biologically friendly (inert) matrix that protects cells from dyes and fluorophores from cellular interferents.
They also contain an analyte and a reference fluorophore. The sensors permit silent report of key biological parameters, accurate ratiometric measurements, and high spatial and temporal resolutions.
Chuahan provided details of a study that used nanosensors sensitive to pH ( acid test.
The sensors contained a polyacrylamide matrix (50-nm in diameter) and composed to two pH-sensitive fluorphores (Oregon Green and carboxyfluorescein), and pH-sensitive rhodamine.
With all three fluorophores, the sensors could make pH sensitive measurements pH 3.5 to pH 7.5.
A calibration curve could be generated by taking a ratio of the intensities of Oregon Green and rhodamine at specific pH.
Chuahan suggested that the accuracy of the nanosensors (+/- 0.17 pH units) makes them ideal for online measurements in biological systems.
They also can provide real-time subcellular analytics and contribute to the optimization of each stage of cell and gene therapy manufacturing.
Chuahan also provided examples of how fluorescent nanosensors can be used to make complex measurements in C. elegan and eukaryotic cell lines.
They also can be used to augment automated analytics in cell and gene manufacturing processes (off-line, on-line, and in-line) by monitoring biochemical subcellular changes.
Erica Brust (Bristol Myers-Squibb) emphasized that the goal of comparability as defined in the ICH Q5E guidance is “to ensure quality, safety, and efficacy of drug products . . . produced through collection and evaluation of relevant data.”
After an overview of ICH Q5E and EMA guidelines, she focused on phase-dependent approaches to comparability, taking into the account the lifecycle of drug products.
For example, first-in-human studies typically do not require comparability studies, but during phase 2 and 3, a risk-based approach should be taken to determine the scope and tiers for comparability assessment.
For paired run studies, risk-developers typically “split either at the source material or further downstream, depending on the nature of the change.”
Burst presented a general risk-based comparability strategy flowchart based on assessment of process control and critical quality attribute assessment and a general approach to beginning a comparability assessment.
One approach to comparability risk assessment is scoring, in which attributes are assigned a number based on potential risk of a change to cause variation in process performance.
Those scores are used to prioritize which aspects to assess in the comparability assessment.
A three-tier approach to comparability risk assessment also has been a successful strategy.
Brust provided and overview of the tiers (generally: tier 1 is equivalence test approach, tier 2 is quality range, tier 3 is visual assessment approach), and concluded with a case study of risk-based comparability assessment for drug product manufacturing site transfer.
